Abstract PR016: Supplement And Medication Use in Early-Onset Colorectal Cancer: An Analysis of the Ohio Colorectal Cancer Prevention Initiative
Bibliographic record
Abstract
Abstract Early-onset colorectal cancer (EOCRC) has increased in the last several decades and now accounts for 10% of new CRC diagnoses in the U.S. Most EOCRC cases are sporadic, with no identified molecular causes that differ from late-onset CRC (LOCRC), suggesting that modifiable environmental factors may have an enhanced role in EOCRC. Despite observed links between supplement and medication use and overall CRC risk, few studies have examined usage in EOCRC, compared usage with LOCRC, or assessed their potential protective effects for EOCRC. To address this gap, we evaluated self-reported supplement and medication use in sporadic EOCRC, compared to LOCRC incidence. We utilized baseline data from the Ohio Colorectal Cancer Prevention Initiative (OCCPI), a statewide initiative to increase access to germline genetic testing for patients with newly diagnosed CRC. OCCPI enrolled 3310 patients from 2013-2016. The current study included 1408 individuals with germline negative CRC and completed baseline questionnaires (n=1408). Model covariates included year of cancer diagnosis, sex, race, education, marital status, employment status, insurance type, and history of other cancer. The primary exposures of interest were the supplements: vitamins A, B-complex, C, D, E, and K, beta-carotene, calcium, iron, magnesium, potassium, selenium, zinc, and fish oil, and the following medications: ACE inhibitors, beta blockers, calcium blocker, digoxin, coumadin, diuretics, anti-diabetic medication, antacids, antidepressants, acetaminophen, and nonsteroidal anti-inflammatory drugs. The outcome of interest was odds of EOCRC, with LOCRC as reference, adjusting for multiple comparisons. Among 260 EOCRC and 1148 LOCRC cases, those with EOCRC were significantly more likely to have graduated college (43.6% v. 30.4%), be single/never married (12.4% v. 6.8%), currently employed (72.3% v. 33.6%), and have private insurance (83.7% v. 40.3%). Individuals with EOCRC were more likely to report having a history of asthma (p=0.003) and less likely to report a history of comorbidities, specifically diverticulitis (p<0.001), heart attack (p<0.001), hepatitis B or C (p=0.04), high cholesterol (p<0.001), stroke (p=0.001), and other cancer(s) (p<0.001). Preliminary analyses suggest that current use of vitamin D (aOR, 0.48; 95%CI, 0.25-0.93) and metformin (aOR, 0.24; 95%CI, 0.19-0.59), was associated with lower odds of developing EOCRC, compared to LOCRC, while current (aOR, 0.39; 95%CI, 0.23-0.67) and past (aOR, 0.48; 95%CI, 0.27-0.86) use of aspirin was associated with lower odds of EOCRC. Current use of antidepressants (aOR, 2.53; 95%CI, 1.55-4.14) was associated with higher odds of developing EOCRC, compared to LOCRC. Further analyses are ongoing. In conclusion, EOCRC patients differ demographically and in supplement and medication use from those with LOCRC. These findings suggest that these exposures may influence EOCRC risk, warranting further investigation. Citation Format: Holli A. Loomans-Kropp, Yevgeniya Gokun, Rand Akasheh, Rachel Pearlman, Cecilia DeGraffinreid, Jo Freudenheim, Peter Shields, Electra D. Paskett. Supplement And Medication Use in Early-Onset Colorectal Cancer: An Analysis of the Ohio Colorectal Cancer Prevention Initiative [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr PR016.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".